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Luigi Di Lillo

2 accepted papers

2025

Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning

CoRL 2025oral

Foundation models can provide robust high-level reasoning on appropriate safety interventions in hazardous scenarios beyond a robot's training data, i.e. out-of-distribution (OOD) failures. However, due to the high inference latency of Large Vision and Language Models, current methods rely on manual…

Cited by 0Source ↗code ↗Scholar ↗
2025

Realistic Extreme Behavior Generation for Improved AV Testing

ICRA 2025

This work introduces a framework to diagnose the strengths and shortcomings of Autonomous Vehicle (AV) collision avoidance technology with synthetic yet realistic potential collision scenarios adapted from real-world, collision-free data. Our framework generates counterfactual collisions with divers

Cited by 3Source ↗Scholar ↗